For instance, Chen et al. proposed a Multi-level Densely Connected Super-Resolution Network (mDCSRN [1]}) with GAN-guided training to generate high-resolution MR images, which can train and inference quickly. In [2]}, a 3D Super-Resolution Convolutional Neural Network (3DSRCNN) is proposed to improve the resolution of 3D-CT volumetric images. In [3]}, Zhao et al. proposed a deep Channel Splitting Network (CSN) to ease the representational burden of deep models and further improve the SR performance of MR images. In [4]}, Peng et al. introduced a Spatially-Aware Interpolation Network (SAINT) for medical slice synthesis to alleviate the memory constraint that volumetric data posed. All of these methods are the cornerstone of building the smart medical system and have great research significance and value.
